Overview

Brought to you by YData

Dataset statistics

Number of variables	36
Number of observations	11113
Missing cells	101546
Missing cells (%)	25.4%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	3.0 MiB
Average record size in memory	281.0 B

Variable types

Numeric	3
Boolean	1
Text	29
Categorical	2
DateTime	1

Alerts

`current` is highly overall correlated with `height` and 1 other fields	High correlation
`height` is highly overall correlated with `current`	High correlation
`weight` is highly overall correlated with `current`	High correlation
`current` is highly imbalanced (99.6%)	Imbalance
`function` is highly imbalanced (87.6%)	Imbalance
`birth_place` has 2386 (21.5%) missing values	Missing
`birth_country` has 1638 (14.7%) missing values	Missing
`residence_place` has 4309 (38.8%) missing values	Missing
`residence_country` has 2825 (25.4%) missing values	Missing
`nickname` has 8147 (73.3%) missing values	Missing
`hobbies` has 6906 (62.1%) missing values	Missing
`occupation` has 1529 (13.8%) missing values	Missing
`education` has 5575 (50.2%) missing values	Missing
`family` has 5552 (50.0%) missing values	Missing
`lang` has 508 (4.6%) missing values	Missing
`coach` has 2891 (26.0%) missing values	Missing
`reason` has 5267 (47.4%) missing values	Missing
`hero` has 7798 (70.2%) missing values	Missing
`influence` has 8958 (80.6%) missing values	Missing
`philosophy` has 8330 (75.0%) missing values	Missing
`sporting_relatives` has 8595 (77.3%) missing values	Missing
`ritual` has 10256 (92.3%) missing values	Missing
`other_sports` has 10053 (90.5%) missing values	Missing
`code` has unique values	Unique
`height` has 6032 (54.3%) zeros	Zeros
`weight` has 10792 (97.1%) zeros	Zeros

Reproduction

Analysis started	2025-03-12 19:35:54.918777
Analysis finished	2025-03-12 19:35:56.689834
Duration	1.77 second
Software version	ydata-profiling vv4.12.2
Download configuration	config.json

code
Real number (ℝ)

Unique

Distinct	11113
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1887418.3

Minimum	1532872
Maximum	9460001
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	86.9 KiB

Quantile statistics

Minimum	1532872
5-th percentile	1543020.6
Q1	1888184
median	1918840
Q3	1948950
95-th percentile	1976498.2
Maximum	9460001
Range	7927129
Interquartile range (IQR)	60766

Descriptive statistics

Standard deviation	358800.59
Coefficient of variation (CV)	0.19010125
Kurtosis	60.717461
Mean	1887418.3
Median Absolute Deviation (MAD)	30453
Skewness	6.4659513
Sum	2.097488 × 10¹⁰
Variance	1.2873786 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1532872	1	< 0.1%
1940310	1	< 0.1%
1940262	1	< 0.1%
1940263	1	< 0.1%
1940264	1	< 0.1%
1940265	1	< 0.1%
1940266	1	< 0.1%
1940267	1	< 0.1%
1940300	1	< 0.1%
1940308	1	< 0.1%
Other values (11103)	11103	99.9%

Value	Count	Frequency (%)
1532872	1	< 0.1%
1532873	1	< 0.1%
1532874	1	< 0.1%
1532944	1	< 0.1%
1532945	1	< 0.1%
1532951	1	< 0.1%
1533112	1	< 0.1%
1533136	1	< 0.1%
1533176	1	< 0.1%
1533188	1	< 0.1%

Value	Count	Frequency (%)
9460001	1	< 0.1%
4986655	1	< 0.1%
4983537	1	< 0.1%
4982762	1	< 0.1%
4982175	1	< 0.1%
4980004	1	< 0.1%
4979790	1	< 0.1%
4979624	1	< 0.1%
4979566	1	< 0.1%
4979565	1	< 0.1%

current
Boolean

High correlation Imbalance

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	11.0 KiB

True	11110
False	3

Value	Count	Frequency (%)
True	11110	> 99.9%
False	3	< 0.1%

name
Text

Distinct	11103
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Memory size	86.9 KiB

Length

Max length	35
Median length	31
Mean length	14.70818
Min length	3

Characters and Unicode

Total characters	163452
Distinct characters	62
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11093 ?
Unique (%)	99.8%

Sample

1st row	ALEKSANYAN Artur
2nd row	AMOYAN Malkhas
3rd row	GALSTYAN Slavik
4th row	HARUTYUNYAN Arsen
5th row	TEVANYAN Vazgen

Value	Count	Frequency (%)
de	105	0.4%
van	97	0.4%
maria	77	0.3%
mohamed	49	0.2%
laura	47	0.2%
lee	43	0.2%
anna	42	0.2%
daniel	42	0.2%
wang	42	0.2%
thomas	41	0.2%
Other values (14854)	23640	97.6%

Most occurring characters

Value	Count	Frequency (%)
	13112	8.0%
A	11091	6.8%
a	10383	6.4%
E	7882	4.8%
i	6707	4.1%
e	6330	3.9%
R	6078	3.7%
O	6036	3.7%
I	6020	3.7%
N	5847	3.6%
Other values (52)	83966	51.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	163452	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	13112	8.0%
A	11091	6.8%
a	10383	6.4%
E	7882	4.8%
i	6707	4.1%
e	6330	3.9%
R	6078	3.7%
O	6036	3.7%
I	6020	3.7%
N	5847	3.6%
Other values (52)	83966	51.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	163452	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	13112	8.0%
A	11091	6.8%
a	10383	6.4%
E	7882	4.8%
i	6707	4.1%
e	6330	3.9%
R	6078	3.7%
O	6036	3.7%
I	6020	3.7%
N	5847	3.6%
Other values (52)	83966	51.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	163452	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	13112	8.0%
A	11091	6.8%
a	10383	6.4%
E	7882	4.8%
i	6707	4.1%
e	6330	3.9%
R	6078	3.7%
O	6036	3.7%
I	6020	3.7%
N	5847	3.6%
Other values (52)	83966	51.4%

name_short
Text

Distinct	10756
Distinct (%)	96.8%
Missing	3
Missing (%)	< 0.1%
Memory size	86.9 KiB

Length

Max length	18
Median length	15
Mean length	9.260216
Min length	3

Characters and Unicode

Total characters	102881
Distinct characters	51
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10499 ?
Unique (%)	94.5%

Sample

1st row	ALEKSANYAN A
2nd row	AMOYAN M
3rd row	GALSTYAN S
4th row	HARUTYUNYAN A
5th row	TEVANYAN V

Value	Count	Frequency (%)
m	1116	4.8%
a	1104	4.8%
s	754	3.3%
j	711	3.1%
l	550	2.4%
e	469	2.0%
k	461	2.0%
c	461	2.0%
t	444	1.9%
d	426	1.9%
Other values (9590)	16531	71.8%

Most occurring characters

Value	Count	Frequency (%)
	11921	11.6%
A	11033	10.7%
E	7851	7.6%
R	6058	5.9%
O	6013	5.8%
I	5990	5.8%
N	5827	5.7%
S	5475	5.3%
L	4908	4.8%
M	4086	4.0%
Other values (41)	33719	32.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	102881	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	11921	11.6%
A	11033	10.7%
E	7851	7.6%
R	6058	5.9%
O	6013	5.8%
I	5990	5.8%
N	5827	5.7%
S	5475	5.3%
L	4908	4.8%
M	4086	4.0%
Other values (41)	33719	32.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	102881	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	11921	11.6%
A	11033	10.7%
E	7851	7.6%
R	6058	5.9%
O	6013	5.8%
I	5990	5.8%
N	5827	5.7%
S	5475	5.3%
L	4908	4.8%
M	4086	4.0%
Other values (41)	33719	32.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	102881	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	11921	11.6%
A	11033	10.7%
E	7851	7.6%
R	6058	5.9%
O	6013	5.8%
I	5990	5.8%
N	5827	5.7%
S	5475	5.3%
L	4908	4.8%
M	4086	4.0%
Other values (41)	33719	32.8%

name_tv
Text

Distinct	11099
Distinct (%)	99.9%
Missing	3
Missing (%)	< 0.1%
Memory size	86.9 KiB

Length

Max length	35
Median length	31
Mean length	14.463276
Min length	3

Characters and Unicode

Total characters	160687
Distinct characters	62
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11088 ?
Unique (%)	99.8%

Sample

1st row	Artur ALEKSANYAN
2nd row	Malkhas AMOYAN
3rd row	Slavik GALSTYAN
4th row	Arsen HARUTYUNYAN
5th row	Vazgen TEVANYAN

Value	Count	Frequency (%)
de	102	0.4%
van	97	0.4%
maria	76	0.3%
laura	47	0.2%
mohamed	43	0.2%
lee	43	0.2%
wang	42	0.2%
daniel	42	0.2%
anna	41	0.2%
kim	39	0.2%
Other values (14742)	23287	97.6%

Most occurring characters

Value	Count	Frequency (%)
	12751	7.9%
A	11037	6.9%
a	10023	6.2%
E	7838	4.9%
i	6506	4.0%
e	6129	3.8%
R	6054	3.8%
O	6019	3.7%
I	6004	3.7%
N	5828	3.6%
Other values (52)	82498	51.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	160687	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	12751	7.9%
A	11037	6.9%
a	10023	6.2%
E	7838	4.9%
i	6506	4.0%
e	6129	3.8%
R	6054	3.8%
O	6019	3.7%
I	6004	3.7%
N	5828	3.6%
Other values (52)	82498	51.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	160687	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	12751	7.9%
A	11037	6.9%
a	10023	6.2%
E	7838	4.9%
i	6506	4.0%
e	6129	3.8%
R	6054	3.8%
O	6019	3.7%
I	6004	3.7%
N	5828	3.6%
Other values (52)	82498	51.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	160687	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	12751	7.9%
A	11037	6.9%
a	10023	6.2%
E	7838	4.9%
i	6506	4.0%
e	6129	3.8%
R	6054	3.8%
O	6019	3.7%
I	6004	3.7%
N	5828	3.6%
Other values (52)	82498	51.3%

gender
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	86.9 KiB

Male	5658
Female	5455

Length

Max length	6
Median length	4
Mean length	4.9817331
Min length	4

Characters and Unicode

Total characters	55362
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Male
2nd row	Male
3rd row	Male
4th row	Male
5th row	Male

Common Values

Value	Count	Frequency (%)
Male	5658	50.9%
Female	5455	49.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
male	5658	50.9%
female	5455	49.1%

Most occurring characters

Value	Count	Frequency (%)
e	16568	29.9%
a	11113	20.1%
l	11113	20.1%
M	5658	10.2%
F	5455	9.9%
m	5455	9.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	55362	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	16568	29.9%
a	11113	20.1%
l	11113	20.1%
M	5658	10.2%
F	5455	9.9%
m	5455	9.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	55362	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	16568	29.9%
a	11113	20.1%
l	11113	20.1%
M	5658	10.2%
F	5455	9.9%
m	5455	9.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	55362	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	16568	29.9%
a	11113	20.1%
l	11113	20.1%
M	5658	10.2%
F	5455	9.9%
m	5455	9.9%

function
Categorical

Imbalance

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	86.9 KiB

Athlete	10924
Alternate Athlete	189

Length

Max length	17
Median length	7
Mean length	7.1700711
Min length	7

Characters and Unicode

Total characters	79681
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Athlete
2nd row	Athlete
3rd row	Athlete
4th row	Athlete
5th row	Athlete

Common Values

Value	Count	Frequency (%)
Athlete	10924	98.3%
Alternate Athlete	189	1.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
athlete	11113	98.3%
alternate	189	1.7%

Most occurring characters

Value	Count	Frequency (%)
t	22604	28.4%
e	22604	28.4%
A	11302	14.2%
l	11302	14.2%
h	11113	13.9%
r	189	0.2%
n	189	0.2%
a	189	0.2%
	189	0.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	79681	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
t	22604	28.4%
e	22604	28.4%
A	11302	14.2%
l	11302	14.2%
h	11113	13.9%
r	189	0.2%
n	189	0.2%
a	189	0.2%
	189	0.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	79681	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
t	22604	28.4%
e	22604	28.4%
A	11302	14.2%
l	11302	14.2%
h	11113	13.9%
r	189	0.2%
n	189	0.2%
a	189	0.2%
	189	0.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	79681	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
t	22604	28.4%
e	22604	28.4%
A	11302	14.2%
l	11302	14.2%
h	11113	13.9%
r	189	0.2%
n	189	0.2%
a	189	0.2%
	189	0.2%

country_code
Text

Distinct	206
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Memory size	86.9 KiB

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	33339
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	< 0.1%

Sample

1st row	ARM
2nd row	ARM
3rd row	ARM
4th row	ARM
5th row	ARM

Value	Count	Frequency (%)
usa	619	5.6%
fra	601	5.4%
aus	475	4.3%
ger	457	4.1%
jpn	431	3.9%
esp	401	3.6%
chn	398	3.6%
ita	397	3.6%
gbr	343	3.1%
can	332	3.0%
Other values (196)	6659	59.9%

Most occurring characters

Value	Count	Frequency (%)
A	3967	11.9%
R	3710	11.1%
N	2697	8.1%
E	2582	7.7%
S	2458	7.4%
U	2393	7.2%
G	1638	4.9%
P	1423	4.3%
I	1377	4.1%
B	1265	3.8%
Other values (16)	9829	29.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	33339	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
A	3967	11.9%
R	3710	11.1%
N	2697	8.1%
E	2582	7.7%
S	2458	7.4%
U	2393	7.2%
G	1638	4.9%
P	1423	4.3%
I	1377	4.1%
B	1265	3.8%
Other values (16)	9829	29.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	33339	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
A	3967	11.9%
R	3710	11.1%
N	2697	8.1%
E	2582	7.7%
S	2458	7.4%
U	2393	7.2%
G	1638	4.9%
P	1423	4.3%
I	1377	4.1%
B	1265	3.8%
Other values (16)	9829	29.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	33339	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
A	3967	11.9%
R	3710	11.1%
N	2697	8.1%
E	2582	7.7%
S	2458	7.4%
U	2393	7.2%
G	1638	4.9%
P	1423	4.3%
I	1377	4.1%
B	1265	3.8%
Other values (16)	9829	29.5%

country
Text

Distinct	206
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Memory size	86.9 KiB

Length

Max length	20
Median length	18
Mean length	7.6967516
Min length	3

Characters and Unicode

Total characters	85534
Distinct characters	57
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	< 0.1%

Sample

1st row	Armenia
2nd row	Armenia
3rd row	Armenia
4th row	Armenia
5th row	Armenia

Value	Count	Frequency (%)
united	619	4.8%
states	619	4.8%
france	601	4.6%
australia	475	3.7%
germany	457	3.5%
china	432	3.3%
japan	431	3.3%
spain	401	3.1%
italy	397	3.1%
great	343	2.6%
Other values (232)	8238	63.3%

Most occurring characters

Value	Count	Frequency (%)
a	13370	15.6%
n	7426	8.7%
e	7205	8.4%
i	6878	8.0%
r	5702	6.7%
t	5167	6.0%
l	3381	4.0%
d	2648	3.1%
o	2451	2.9%
s	2189	2.6%
Other values (47)	29117	34.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	85534	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	13370	15.6%
n	7426	8.7%
e	7205	8.4%
i	6878	8.0%
r	5702	6.7%
t	5167	6.0%
l	3381	4.0%
d	2648	3.1%
o	2451	2.9%
s	2189	2.6%
Other values (47)	29117	34.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	85534	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	13370	15.6%
n	7426	8.7%
e	7205	8.4%
i	6878	8.0%
r	5702	6.7%
t	5167	6.0%
l	3381	4.0%
d	2648	3.1%
o	2451	2.9%
s	2189	2.6%
Other values (47)	29117	34.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	85534	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	13370	15.6%
n	7426	8.7%
e	7205	8.4%
i	6878	8.0%
r	5702	6.7%
t	5167	6.0%
l	3381	4.0%
d	2648	3.1%
o	2451	2.9%
s	2189	2.6%
Other values (47)	29117	34.0%

country_long
Text

Distinct	206
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Memory size	86.9 KiB

Length

Max length	37
Median length	32
Mean length	9.4523531
Min length	3

Characters and Unicode

Total characters	105044
Distinct characters	56
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	< 0.1%

Sample

1st row	Armenia
2nd row	Armenia
3rd row	Armenia
4th row	Armenia
5th row	Armenia

Value	Count	Frequency (%)
of	1265	7.9%
republic	716	4.5%
united	639	4.0%
states	622	3.9%
america	619	3.9%
france	601	3.7%
australia	475	3.0%
germany	457	2.8%
china	432	2.7%
japan	431	2.7%
Other values (235)	9789	61.0%

Most occurring characters

Value	Count	Frequency (%)
a	14143	13.5%
e	9501	9.0%
i	8265	7.9%
n	7471	7.1%
r	6375	6.1%
t	5238	5.0%
	4933	4.7%
l	4510	4.3%
o	4134	3.9%
c	2932	2.8%
Other values (46)	37542	35.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	105044	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	14143	13.5%
e	9501	9.0%
i	8265	7.9%
n	7471	7.1%
r	6375	6.1%
t	5238	5.0%
	4933	4.7%
l	4510	4.3%
o	4134	3.9%
c	2932	2.8%
Other values (46)	37542	35.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	105044	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	14143	13.5%
e	9501	9.0%
i	8265	7.9%
n	7471	7.1%
r	6375	6.1%
t	5238	5.0%
	4933	4.7%
l	4510	4.3%
o	4134	3.9%
c	2932	2.8%
Other values (46)	37542	35.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	105044	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	14143	13.5%
e	9501	9.0%
i	8265	7.9%
n	7471	7.1%
r	6375	6.1%
t	5238	5.0%
	4933	4.7%
l	4510	4.3%
o	4134	3.9%
c	2932	2.8%
Other values (46)	37542	35.7%

nationality
Text

Distinct	197
Distinct (%)	1.8%
Missing	3
Missing (%)	< 0.1%
Memory size	86.9 KiB

Length

Max length	20
Median length	18
Mean length	7.7594959
Min length	4

Characters and Unicode

Total characters	86208
Distinct characters	57
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	< 0.1%

Sample

1st row	Armenia
2nd row	Armenia
3rd row	Armenia
4th row	Armenia
5th row	Armenia

Value	Count	Frequency (%)
united	696	5.3%
states	696	5.3%
france	607	4.6%
australia	476	3.6%
germany	457	3.5%
china	432	3.3%
japan	431	3.3%
spain	403	3.1%
italy	397	3.0%
great	357	2.7%
Other values (222)	8104	62.1%

Most occurring characters

Value	Count	Frequency (%)
a	13520	15.7%
n	7554	8.8%
e	7382	8.6%
i	6928	8.0%
r	5718	6.6%
t	5398	6.3%
l	3388	3.9%
d	2734	3.2%
o	2352	2.7%
s	2293	2.7%
Other values (47)	28941	33.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	86208	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	13520	15.7%
n	7554	8.8%
e	7382	8.6%
i	6928	8.0%
r	5718	6.6%
t	5398	6.3%
l	3388	3.9%
d	2734	3.2%
o	2352	2.7%
s	2293	2.7%
Other values (47)	28941	33.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	86208	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	13520	15.7%
n	7554	8.8%
e	7382	8.6%
i	6928	8.0%
r	5718	6.6%
t	5398	6.3%
l	3388	3.9%
d	2734	3.2%
o	2352	2.7%
s	2293	2.7%
Other values (47)	28941	33.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	86208	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	13520	15.7%
n	7554	8.8%
e	7382	8.6%
i	6928	8.0%
r	5718	6.6%
t	5398	6.3%
l	3388	3.9%
d	2734	3.2%
o	2352	2.7%
s	2293	2.7%
Other values (47)	28941	33.6%

nationality_long
Text

Distinct	197
Distinct (%)	1.8%
Missing	3
Missing (%)	< 0.1%
Memory size	86.9 KiB

Length

Max length	37
Median length	32
Mean length	9.5625563
Min length	4

Characters and Unicode

Total characters	106240
Distinct characters	56
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	< 0.1%

Sample

1st row	Armenia
2nd row	Armenia
3rd row	Armenia
4th row	Armenia
5th row	Armenia

Value	Count	Frequency (%)
of	1357	8.4%
republic	733	4.5%
united	716	4.4%
states	699	4.3%
america	696	4.3%
france	607	3.7%
australia	476	2.9%
germany	457	2.8%
china	432	2.7%
japan	431	2.7%
Other values (223)	9602	59.2%

Most occurring characters

Value	Count	Frequency (%)
a	14352	13.5%
e	9628	9.1%
i	8382	7.9%
n	7603	7.2%
r	6470	6.1%
t	5466	5.1%
	5096	4.8%
l	4514	4.2%
o	4128	3.9%
c	2947	2.8%
Other values (46)	37654	35.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	106240	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	14352	13.5%
e	9628	9.1%
i	8382	7.9%
n	7603	7.2%
r	6470	6.1%
t	5466	5.1%
	5096	4.8%
l	4514	4.2%
o	4128	3.9%
c	2947	2.8%
Other values (46)	37654	35.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	106240	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	14352	13.5%
e	9628	9.1%
i	8382	7.9%
n	7603	7.2%
r	6470	6.1%
t	5466	5.1%
	5096	4.8%
l	4514	4.2%
o	4128	3.9%
c	2947	2.8%
Other values (46)	37654	35.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	106240	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	14352	13.5%
e	9628	9.1%
i	8382	7.9%
n	7603	7.2%
r	6470	6.1%
t	5466	5.1%
	5096	4.8%
l	4514	4.2%
o	4128	3.9%
c	2947	2.8%
Other values (46)	37654	35.4%

nationality_code
Text

Distinct	197
Distinct (%)	1.8%
Missing	3
Missing (%)	< 0.1%
Memory size	86.9 KiB

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	33330
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	< 0.1%

Sample

1st row	ARM
2nd row	ARM
3rd row	ARM
4th row	ARM
5th row	ARM

Value	Count	Frequency (%)
usa	696	6.3%
fra	607	5.5%
aus	476	4.3%
ger	457	4.1%
jpn	431	3.9%
esp	403	3.6%
chn	398	3.6%
ita	397	3.6%
gbr	357	3.2%
can	336	3.0%
Other values (187)	6552	59.0%

Most occurring characters

Value	Count	Frequency (%)
A	4000	12.0%
R	3677	11.0%
N	2675	8.0%
S	2558	7.7%
E	2550	7.7%
U	2423	7.3%
G	1645	4.9%
P	1373	4.1%
I	1355	4.1%
B	1286	3.9%
Other values (16)	9788	29.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	33330	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
A	4000	12.0%
R	3677	11.0%
N	2675	8.0%
S	2558	7.7%
E	2550	7.7%
U	2423	7.3%
G	1645	4.9%
P	1373	4.1%
I	1355	4.1%
B	1286	3.9%
Other values (16)	9788	29.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	33330	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
A	4000	12.0%
R	3677	11.0%
N	2675	8.0%
S	2558	7.7%
E	2550	7.7%
U	2423	7.3%
G	1645	4.9%
P	1373	4.1%
I	1355	4.1%
B	1286	3.9%
Other values (16)	9788	29.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	33330	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
A	4000	12.0%
R	3677	11.0%
N	2675	8.0%
S	2558	7.7%
E	2550	7.7%
U	2423	7.3%
G	1645	4.9%
P	1373	4.1%
I	1355	4.1%
B	1286	3.9%
Other values (16)	9788	29.4%

height
Real number (ℝ)

High correlation Zeros

Distinct	74
Distinct (%)	0.7%
Missing	3
Missing (%)	< 0.1%
Infinite	0
Infinite (%)	0.0%
Mean	81.79883

Minimum	0
Maximum	222
Zeros	6032
Zeros (%)	54.3%
Negative	0
Negative (%)	0.0%
Memory size	86.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	177
95-th percentile	194
Maximum	222
Range	222
Interquartile range (IQR)	177

Descriptive statistics

Standard deviation	89.508247
Coefficient of variation (CV)	1.0942485
Kurtosis	-1.9298165
Mean	81.79883
Median Absolute Deviation (MAD)	0
Skewness	0.19618422
Sum	908785
Variance	8011.7263
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	6032	54.3%
170	291	2.6%
180	246	2.2%
175	237	2.1%
178	206	1.9%
185	189	1.7%
183	186	1.7%
190	163	1.5%
182	156	1.4%
168	156	1.4%
Other values (64)	3248	29.2%

Value	Count	Frequency (%)
0	6032	54.3%
140	1	< 0.1%
147	1	< 0.1%
148	1	< 0.1%
149	2	< 0.1%
150	6	0.1%
151	1	< 0.1%
152	16	0.1%
153	7	0.1%
154	9	0.1%

Value	Count	Frequency (%)
222	1	< 0.1%
217	1	< 0.1%
216	3	< 0.1%
215	1	< 0.1%
214	1	< 0.1%
213	2	< 0.1%
212	3	< 0.1%
211	12	0.1%
210	7	0.1%
209	2	< 0.1%

weight
Real number (ℝ)

High correlation Zeros

Distinct	55
Distinct (%)	0.5%
Missing	5
Missing (%)	< 0.1%
Infinite	0
Infinite (%)	0.0%
Mean	2.2119193

Minimum	0
Maximum	113
Zeros	10792
Zeros (%)	97.1%
Negative	0
Negative (%)	0.0%
Memory size	86.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	113
Range	113
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	13.109608
Coefficient of variation (CV)	5.9268018
Kurtosis	34.109539
Mean	2.2119193
Median Absolute Deviation (MAD)	0
Skewness	5.9248041
Sum	24570
Variance	171.86181
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	10792	97.1%
70	20	0.2%
68	14	0.1%
65	14	0.1%
85	14	0.1%
90	12	0.1%
95	10	0.1%
78	10	0.1%
75	9	0.1%
63	9	0.1%
Other values (45)	204	1.8%

Value	Count	Frequency (%)
0	10792	97.1%
51	1	< 0.1%
52	1	< 0.1%
54	1	< 0.1%
55	1	< 0.1%
56	4	< 0.1%
57	2	< 0.1%
58	2	< 0.1%
59	3	< 0.1%
60	9	0.1%

Value	Count	Frequency (%)
113	1	< 0.1%
106	2	< 0.1%
105	4	< 0.1%
102	2	< 0.1%
101	2	< 0.1%
100	6	0.1%
99	2	< 0.1%
98	6	0.1%
97	1	< 0.1%
96	3	< 0.1%

disciplines
Text

Distinct	52
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	86.9 KiB

Length

Max length	41
Median length	32
Mean length	13.35031
Min length	8

Characters and Unicode

Total characters	148362
Distinct characters	47
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	< 0.1%

Sample

1st row	['Wrestling']
2nd row	['Wrestling']
3rd row	['Wrestling']
4th row	['Wrestling']
5th row	['Wrestling']

Value	Count	Frequency (%)
athletics	2020	14.7%
swimming	1014	7.4%
cycling	584	4.2%
football	553	4.0%
rowing	493	3.6%
hockey	415	3.0%
volleyball	407	3.0%
handball	386	2.8%
judo	378	2.7%
basketball	353	2.6%
Other values (43)	7166	52.0%

Most occurring characters

Value	Count	Frequency (%)
'	22284	15.0%
[	11113	7.5%
]	11113	7.5%
i	10228	6.9%
l	8616	5.8%
t	8329	5.6%
n	7948	5.4%
e	6677	4.5%
o	6030	4.1%
a	5695	3.8%
Other values (37)	50329	33.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	148362	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
'	22284	15.0%
[	11113	7.5%
]	11113	7.5%
i	10228	6.9%
l	8616	5.8%
t	8329	5.6%
n	7948	5.4%
e	6677	4.5%
o	6030	4.1%
a	5695	3.8%
Other values (37)	50329	33.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	148362	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
'	22284	15.0%
[	11113	7.5%
]	11113	7.5%
i	10228	6.9%
l	8616	5.8%
t	8329	5.6%
n	7948	5.4%
e	6677	4.5%
o	6030	4.1%
a	5695	3.8%
Other values (37)	50329	33.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	148362	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
'	22284	15.0%
[	11113	7.5%
]	11113	7.5%
i	10228	6.9%
l	8616	5.8%
t	8329	5.6%
n	7948	5.4%
e	6677	4.5%
o	6030	4.1%
a	5695	3.8%
Other values (37)	50329	33.9%

events
Text

Distinct	643
Distinct (%)	5.8%
Missing	0
Missing (%)	0.0%
Memory size	86.9 KiB

Length

Max length	225
Median length	167
Mean length	25.054081
Min length	7

Characters and Unicode

Total characters	278426
Distinct characters	68
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	172 ?
Unique (%)	1.5%

Sample

1st row	["Men's Greco-Roman 97kg"]
2nd row	["Men's Greco-Roman 77kg"]
3rd row	["Men's Greco-Roman 67kg"]
4th row	["Men's Freestyle 57kg"]
5th row	["Men's Freestyle 65kg"]

Value	Count	Frequency (%)
men's	4774	12.8%
women's	4484	12.0%
men	2050	5.5%
women	1950	5.2%
team	1285	3.4%
relay	1281	3.4%
100m	1138	3.0%
x	1049	2.8%
4	1049	2.8%
individual	1046	2.8%
Other values (159)	17323	46.3%

Most occurring characters

Value	Count	Frequency (%)
	26316	9.5%
e	26241	9.4%
'	20522	7.4%
"	18514	6.6%
n	17764	6.4%
s	13527	4.9%
m	12820	4.6%
[	11113	4.0%
]	11113	4.0%
o	10682	3.8%
Other values (58)	109814	39.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	278426	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	26316	9.5%
e	26241	9.4%
'	20522	7.4%
"	18514	6.6%
n	17764	6.4%
s	13527	4.9%
m	12820	4.6%
[	11113	4.0%
]	11113	4.0%
o	10682	3.8%
Other values (58)	109814	39.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	278426	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	26316	9.5%
e	26241	9.4%
'	20522	7.4%
"	18514	6.6%
n	17764	6.4%
s	13527	4.9%
m	12820	4.6%
[	11113	4.0%
]	11113	4.0%
o	10682	3.8%
Other values (58)	109814	39.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	278426	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	26316	9.5%
e	26241	9.4%
'	20522	7.4%
"	18514	6.6%
n	17764	6.4%
s	13527	4.9%
m	12820	4.6%
[	11113	4.0%
]	11113	4.0%
o	10682	3.8%
Other values (58)	109814	39.4%

birth_date
Date

Distinct	5518
Distinct (%)	49.7%
Missing	0
Missing (%)	0.0%
Memory size	86.9 KiB

Minimum	1954-12-01 00:00:00
Maximum	2012-08-11 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

birth_place
Text

Missing

Distinct	4725
Distinct (%)	54.1%
Missing	2386
Missing (%)	21.5%
Memory size	86.9 KiB

Length

Max length	44
Median length	33
Mean length	9.1250143
Min length	2

Characters and Unicode

Total characters	79634
Distinct characters	36
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3488 ?
Unique (%)	40.0%

Sample

1st row	GYUMRI
2nd row	YEREVAN
3rd row	MASIS
4th row	POKR VEDI
5th row	PEREIRA

Value	Count	Frequency (%)
ca	136	1.1%
de	126	1.1%
nsw	118	1.0%
on	118	1.0%
vic	88	0.7%
san	82	0.7%
city	78	0.7%
qld	75	0.6%
budapest	66	0.6%
la	61	0.5%
Other values (5001)	11002	92.1%

Most occurring characters

Value	Count	Frequency (%)
A	9623	12.1%
E	6401	8.0%
N	6344	8.0%
O	5713	7.2%
I	5018	6.3%
R	4875	6.1%
S	4288	5.4%
L	4022	5.1%
T	3630	4.6%
	3223	4.0%
Other values (26)	26497	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	79634	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
A	9623	12.1%
E	6401	8.0%
N	6344	8.0%
O	5713	7.2%
I	5018	6.3%
R	4875	6.1%
S	4288	5.4%
L	4022	5.1%
T	3630	4.6%
	3223	4.0%
Other values (26)	26497	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	79634	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
A	9623	12.1%
E	6401	8.0%
N	6344	8.0%
O	5713	7.2%
I	5018	6.3%
R	4875	6.1%
S	4288	5.4%
L	4022	5.1%
T	3630	4.6%
	3223	4.0%
Other values (26)	26497	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	79634	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
A	9623	12.1%
E	6401	8.0%
N	6344	8.0%
O	5713	7.2%
I	5018	6.3%
R	4875	6.1%
S	4288	5.4%
L	4022	5.1%
T	3630	4.6%
	3223	4.0%
Other values (26)	26497	33.3%

birth_country
Text

Missing

Distinct	205
Distinct (%)	2.2%
Missing	1638
Missing (%)	14.7%
Memory size	86.9 KiB

Length

Max length	20
Median length	18
Mean length	7.9003694
Min length	4

Characters and Unicode

Total characters	74856
Distinct characters	59
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	22 ?
Unique (%)	0.2%

Sample

1st row	Armenia
2nd row	Armenia
3rd row	Armenia
4th row	Armenia
5th row	Colombia

Value	Count	Frequency (%)
united	705	6.2%
states	705	6.2%
france	552	4.9%
china	397	3.5%
germany	396	3.5%
japan	393	3.5%
australia	391	3.4%
italy	353	3.1%
spain	341	3.0%
great	338	3.0%
Other values (231)	6783	59.7%

Most occurring characters

Value	Count	Frequency (%)
a	11573	15.5%
n	6642	8.9%
e	6569	8.8%
i	6091	8.1%
t	4974	6.6%
r	4854	6.5%
l	2785	3.7%
d	2412	3.2%
s	2094	2.8%
o	2032	2.7%
Other values (49)	24830	33.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	74856	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	11573	15.5%
n	6642	8.9%
e	6569	8.8%
i	6091	8.1%
t	4974	6.6%
r	4854	6.5%
l	2785	3.7%
d	2412	3.2%
s	2094	2.8%
o	2032	2.7%
Other values (49)	24830	33.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	74856	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	11573	15.5%
n	6642	8.9%
e	6569	8.8%
i	6091	8.1%
t	4974	6.6%
r	4854	6.5%
l	2785	3.7%
d	2412	3.2%
s	2094	2.8%
o	2032	2.7%
Other values (49)	24830	33.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	74856	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	11573	15.5%
n	6642	8.9%
e	6569	8.8%
i	6091	8.1%
t	4974	6.6%
r	4854	6.5%
l	2785	3.7%
d	2412	3.2%
s	2094	2.8%
o	2032	2.7%
Other values (49)	24830	33.2%

residence_place
Text

Missing

Distinct	2752
Distinct (%)	40.4%
Missing	4309
Missing (%)	38.8%
Memory size	86.9 KiB

Length

Max length	37
Median length	30
Mean length	8.9594356
Min length	2

Characters and Unicode

Total characters	60960
Distinct characters	38
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1957 ?
Unique (%)	28.8%

Sample

1st row	GYUMRI
2nd row	YEREVAN
3rd row	YEREVAN
4th row	YEREVAN
5th row	MELBOURNE

Value	Count	Frequency (%)
ca	140	1.5%
fl	122	1.3%
tx	94	1.0%
paris	93	1.0%
beijing	87	0.9%
nsw	84	0.9%
qld	81	0.9%
on	76	0.8%
san	70	0.8%
madrid	64	0.7%
Other values (2992)	8359	90.2%

Most occurring characters

Value	Count	Frequency (%)
A	7019	11.5%
E	4931	8.1%
N	4732	7.8%
O	4278	7.0%
I	3774	6.2%
R	3659	6.0%
L	3438	5.6%
S	3289	5.4%
T	2870	4.7%
	2466	4.0%
Other values (28)	20504	33.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	60960	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
A	7019	11.5%
E	4931	8.1%
N	4732	7.8%
O	4278	7.0%
I	3774	6.2%
R	3659	6.0%
L	3438	5.6%
S	3289	5.4%
T	2870	4.7%
	2466	4.0%
Other values (28)	20504	33.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	60960	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
A	7019	11.5%
E	4931	8.1%
N	4732	7.8%
O	4278	7.0%
I	3774	6.2%
R	3659	6.0%
L	3438	5.6%
S	3289	5.4%
T	2870	4.7%
	2466	4.0%
Other values (28)	20504	33.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	60960	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
A	7019	11.5%
E	4931	8.1%
N	4732	7.8%
O	4278	7.0%
I	3774	6.2%
R	3659	6.0%
L	3438	5.6%
S	3289	5.4%
T	2870	4.7%
	2466	4.0%
Other values (28)	20504	33.6%

residence_country
Text

Missing

Distinct	177
Distinct (%)	2.1%
Missing	2825
Missing (%)	25.4%
Memory size	86.9 KiB

Length

Max length	20
Median length	18
Mean length	8.0878378
Min length	4

Characters and Unicode

Total characters	67032
Distinct characters	56
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	29 ?
Unique (%)	0.3%

Sample

1st row	Armenia
2nd row	Armenia
3rd row	Armenia
4th row	Armenia
5th row	Armenia

Value	Count	Frequency (%)
united	979	9.7%
states	979	9.7%
france	520	5.1%
germany	437	4.3%
spain	383	3.8%
australia	354	3.5%
great	348	3.4%
britain	348	3.4%
china	340	3.4%
italy	314	3.1%
Other values (197)	5138	50.7%

Most occurring characters

Value	Count	Frequency (%)
a	9975	14.9%
e	6107	9.1%
n	5958	8.9%
t	5513	8.2%
i	5305	7.9%
r	4274	6.4%
d	2355	3.5%
l	2337	3.5%
s	2076	3.1%
	1852	2.8%
Other values (46)	21280	31.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	67032	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	9975	14.9%
e	6107	9.1%
n	5958	8.9%
t	5513	8.2%
i	5305	7.9%
r	4274	6.4%
d	2355	3.5%
l	2337	3.5%
s	2076	3.1%
	1852	2.8%
Other values (46)	21280	31.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	67032	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	9975	14.9%
e	6107	9.1%
n	5958	8.9%
t	5513	8.2%
i	5305	7.9%
r	4274	6.4%
d	2355	3.5%
l	2337	3.5%
s	2076	3.1%
	1852	2.8%
Other values (46)	21280	31.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	67032	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	9975	14.9%
e	6107	9.1%
n	5958	8.9%
t	5513	8.2%
i	5305	7.9%
r	4274	6.4%
d	2355	3.5%
l	2337	3.5%
s	2076	3.1%
	1852	2.8%
Other values (46)	21280	31.7%

nickname
Text

Missing

Distinct	2623
Distinct (%)	88.4%
Missing	8147
Missing (%)	73.3%
Memory size	86.9 KiB

Length

Max length	369
Median length	305
Mean length	15.813554
Min length	1

Characters and Unicode

Total characters	46903
Distinct characters	96
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2422 ?
Unique (%)	81.7%

Sample

1st row	White Bear
2nd row	Bad Boy
3rd row	Earlier in her career she was nicknamed the 'Poor Olympian' due to the financial challenges she faced
4th row	Diamante Negro (Black Diamond), Martillo Xalapeno (Hammer from Xalapa, given to him by Spanish triathlete Javier Gomez Noya)
5th row	Nutria ("Otter" in Spanish)

Value	Count	Frequency (%)
the	348	4.1%
of	113	1.3%
to	99	1.2%
a	89	1.1%
his	82	1.0%
in	78	0.9%
her	76	0.9%
and	68	0.8%
because	64	0.8%
little	56	0.7%
Other values (4192)	7328	87.2%

Most occurring characters

Value	Count	Frequency (%)
	5443	11.6%
e	3991	8.5%
a	3826	8.2%
i	3026	6.5%
o	2587	5.5%
n	2442	5.2%
t	2084	4.4%
r	2009	4.3%
s	1684	3.6%
l	1640	3.5%
Other values (86)	18171	38.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	46903	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	5443	11.6%
e	3991	8.5%
a	3826	8.2%
i	3026	6.5%
o	2587	5.5%
n	2442	5.2%
t	2084	4.4%
r	2009	4.3%
s	1684	3.6%
l	1640	3.5%
Other values (86)	18171	38.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	46903	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	5443	11.6%
e	3991	8.5%
a	3826	8.2%
i	3026	6.5%
o	2587	5.5%
n	2442	5.2%
t	2084	4.4%
r	2009	4.3%
s	1684	3.6%
l	1640	3.5%
Other values (86)	18171	38.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	46903	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	5443	11.6%
e	3991	8.5%
a	3826	8.2%
i	3026	6.5%
o	2587	5.5%
n	2442	5.2%
t	2084	4.4%
r	2009	4.3%
s	1684	3.6%
l	1640	3.5%
Other values (86)	18171	38.7%

hobbies
Text

Missing

Distinct	3405
Distinct (%)	80.9%
Missing	6906
Missing (%)	62.1%
Memory size	86.9 KiB

Length

Max length	540
Median length	284
Mean length	46.12812
Min length	3

Characters and Unicode

Total characters	194061
Distinct characters	86
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3241 ?
Unique (%)	77.0%

Sample

1st row	Playing and watching football
2nd row	Music
3rd row	Running, watching movies, football, chatting with friends
4th row	Music, films
5th row	Spending time with friends, playing the piano, going to the cinema

Value	Count	Frequency (%)
and	1102	3.9%
to	838	3.0%
with	812	2.9%
playing	771	2.7%
reading	703	2.5%
the	670	2.4%
watching	662	2.3%
time	651	2.3%
music	626	2.2%
spending	616	2.2%
Other values (3268)	20826	73.6%

Most occurring characters

Value	Count	Frequency (%)
	24075	12.4%
i	18262	9.4%
n	15906	8.2%
e	12591	6.5%
a	11942	6.2%
g	10552	5.4%
t	10219	5.3%
o	10058	5.2%
s	9160	4.7%
l	7074	3.6%
Other values (76)	64222	33.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	194061	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	24075	12.4%
i	18262	9.4%
n	15906	8.2%
e	12591	6.5%
a	11942	6.2%
g	10552	5.4%
t	10219	5.3%
o	10058	5.2%
s	9160	4.7%
l	7074	3.6%
Other values (76)	64222	33.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	194061	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	24075	12.4%
i	18262	9.4%
n	15906	8.2%
e	12591	6.5%
a	11942	6.2%
g	10552	5.4%
t	10219	5.3%
o	10058	5.2%
s	9160	4.7%
l	7074	3.6%
Other values (76)	64222	33.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	194061	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	24075	12.4%
i	18262	9.4%
n	15906	8.2%
e	12591	6.5%
a	11942	6.2%
g	10552	5.4%
t	10219	5.3%
o	10058	5.2%
s	9160	4.7%
l	7074	3.6%
Other values (76)	64222	33.1%

occupation
Text

Missing

Distinct	927
Distinct (%)	9.7%
Missing	1529
Missing (%)	13.8%
Memory size	86.9 KiB

Length

Max length	290
Median length	7
Mean length	12.421432
Min length	4

Characters and Unicode

Total characters	119047
Distinct characters	79
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	783 ?
Unique (%)	8.2%

Sample

1st row	Athlete
2nd row	Athlete
3rd row	Athlete
4th row	Athlete
5th row	Athlete

Value	Count	Frequency (%)
athlete	9102	55.6%
student	1297	7.9%
coach	338	2.1%
trainer	197	1.2%
horse	182	1.1%
soldier	170	1.0%
the	161	1.0%
business	153	0.9%
in	148	0.9%
police	147	0.9%
Other values (1330)	4472	27.3%

Most occurring characters

Value	Count	Frequency (%)
e	23733	19.9%
t	23129	19.4%
h	10341	8.7%
l	10297	8.6%
A	9194	7.7%
	6783	5.7%
n	3685	3.1%
r	3629	3.0%
s	3594	3.0%
a	2993	2.5%
Other values (69)	21669	18.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	119047	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	23733	19.9%
t	23129	19.4%
h	10341	8.7%
l	10297	8.6%
A	9194	7.7%
	6783	5.7%
n	3685	3.1%
r	3629	3.0%
s	3594	3.0%
a	2993	2.5%
Other values (69)	21669	18.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	119047	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	23733	19.9%
t	23129	19.4%
h	10341	8.7%
l	10297	8.6%
A	9194	7.7%
	6783	5.7%
n	3685	3.1%
r	3629	3.0%
s	3594	3.0%
a	2993	2.5%
Other values (69)	21669	18.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	119047	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	23733	19.9%
t	23129	19.4%
h	10341	8.7%
l	10297	8.6%
A	9194	7.7%
	6783	5.7%
n	3685	3.1%
r	3629	3.0%
s	3594	3.0%
a	2993	2.5%
Other values (69)	21669	18.2%

education
Text

Missing

Distinct	5352
Distinct (%)	96.6%
Missing	5575
Missing (%)	50.2%
Memory size	86.9 KiB

Length

Max length	384
Median length	264
Mean length	83.559227
Min length	6

Characters and Unicode

Total characters	462751
Distinct characters	107
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5226 ?
Unique (%)	94.4%

Sample

1st row	Graduated from Shirak State University (Gyumri, ARM)
2nd row	Graduated with a Master's degree from the Armenian State Institute of Physical Culture and Sport (2023)
3rd row	Studied at the Armenian State Institute of Physical Culture and Sport (Yerevan, ARM)
4th row	Physical Education at Jaime Isaza Cadavid Colombian Polytechnic, Medellin (COL)
5th row	Studied Medicine at the University of Guadalajara (MEX)

Value	Count	Frequency (%)
university	4829	7.2%
at	3413	5.1%
in	3372	5.0%
of	3162	4.7%
a	1905	2.8%
degree	1734	2.6%
the	1648	2.5%
and	1648	2.5%
from	1523	2.3%
usa	1429	2.1%
Other values (4773)	42202	63.1%

Most occurring characters

Value	Count	Frequency (%)
	61347	13.3%
e	36697	7.9%
i	34785	7.5%
a	28744	6.2%
t	28563	6.2%
n	28098	6.1%
r	22333	4.8%
o	21087	4.6%
s	18593	4.0%
d	14767	3.2%
Other values (97)	167737	36.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	462751	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	61347	13.3%
e	36697	7.9%
i	34785	7.5%
a	28744	6.2%
t	28563	6.2%
n	28098	6.1%
r	22333	4.8%
o	21087	4.6%
s	18593	4.0%
d	14767	3.2%
Other values (97)	167737	36.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	462751	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	61347	13.3%
e	36697	7.9%
i	34785	7.5%
a	28744	6.2%
t	28563	6.2%
n	28098	6.1%
r	22333	4.8%
o	21087	4.6%
s	18593	4.0%
d	14767	3.2%
Other values (97)	167737	36.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	462751	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	61347	13.3%
e	36697	7.9%
i	34785	7.5%
a	28744	6.2%
t	28563	6.2%
n	28098	6.1%
r	22333	4.8%
o	21087	4.6%
s	18593	4.0%
d	14767	3.2%
Other values (97)	167737	36.2%

family
Text

Missing

Distinct	5447
Distinct (%)	98.0%
Missing	5552
Missing (%)	50.0%
Memory size	86.9 KiB

Length

Max length	322
Median length	179
Mean length	52.189354
Min length	4

Characters and Unicode

Total characters	290225
Distinct characters	103
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5380 ?
Unique (%)	96.7%

Sample

1st row	Father, Gevorg Aleksanyan
2nd row	Wife, Diana (married October 2022). Daughter, Marias (born 2023)
3rd row	Wife, Sona (married November 2023)
4th row	Father, Jose Otoniel. Mother, Maria Rudy. Has three siblings
5th row	One daughter, Lana-Rose, who lives in France

Value	Count	Frequency (%)
father	3251	8.0%
mother	3057	7.6%
brother	1480	3.7%
sister	1329	3.3%
and	954	2.4%
wife	732	1.8%
older	709	1.8%
partner	658	1.6%
born	567	1.4%
younger	507	1.3%
Other values (9526)	27150	67.2%

Most occurring characters

Value	Count	Frequency (%)
	34852	12.0%
e	26928	9.3%
r	24588	8.5%
a	21582	7.4%
t	15938	5.5%
n	14205	4.9%
o	14098	4.9%
i	14078	4.9%
,	12976	4.5%
h	12525	4.3%
Other values (93)	98455	33.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	290225	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	34852	12.0%
e	26928	9.3%
r	24588	8.5%
a	21582	7.4%
t	15938	5.5%
n	14205	4.9%
o	14098	4.9%
i	14078	4.9%
,	12976	4.5%
h	12525	4.3%
Other values (93)	98455	33.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	290225	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	34852	12.0%
e	26928	9.3%
r	24588	8.5%
a	21582	7.4%
t	15938	5.5%
n	14205	4.9%
o	14098	4.9%
i	14078	4.9%
,	12976	4.5%
h	12525	4.3%
Other values (93)	98455	33.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	290225	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	34852	12.0%
e	26928	9.3%
r	24588	8.5%
a	21582	7.4%
t	15938	5.5%
n	14205	4.9%
o	14098	4.9%
i	14078	4.9%
,	12976	4.5%
h	12525	4.3%
Other values (93)	98455	33.9%

lang
Text

Missing

Distinct	738
Distinct (%)	7.0%
Missing	508
Missing (%)	4.6%
Memory size	86.9 KiB

Length

Max length	67
Median length	56
Mean length	11.447148
Min length	1

Characters and Unicode

Total characters	121397
Distinct characters	58
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	449 ?
Unique (%)	4.2%

Sample

1st row	Armenian, English, Russian
2nd row	Armenian
3rd row	Armenian
4th row	Armenian
5th row	Armenian, Russian

Value	Count	Frequency (%)
english	6176	38.8%
spanish	1373	8.6%
french	1243	7.8%
german	820	5.2%
italian	519	3.3%
mandarin	494	3.1%
japanese	441	2.8%
portuguese	416	2.6%
russian	409	2.6%
dutch	402	2.5%
Other values (201)	3613	22.7%

Most occurring characters

Value	Count	Frequency (%)
n	14797	12.2%
i	12194	10.0%
h	10283	8.5%
s	10215	8.4%
a	8953	7.4%
l	7375	6.1%
g	7117	5.9%
E	6205	5.1%
e	5471	4.5%
	5301	4.4%
Other values (48)	33486	27.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	121397	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	14797	12.2%
i	12194	10.0%
h	10283	8.5%
s	10215	8.4%
a	8953	7.4%
l	7375	6.1%
g	7117	5.9%
E	6205	5.1%
e	5471	4.5%
	5301	4.4%
Other values (48)	33486	27.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	121397	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	14797	12.2%
i	12194	10.0%
h	10283	8.5%
s	10215	8.4%
a	8953	7.4%
l	7375	6.1%
g	7117	5.9%
E	6205	5.1%
e	5471	4.5%
	5301	4.4%
Other values (48)	33486	27.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	121397	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	14797	12.2%
i	12194	10.0%
h	10283	8.5%
s	10215	8.4%
a	8953	7.4%
l	7375	6.1%
g	7117	5.9%
E	6205	5.1%
e	5471	4.5%
	5301	4.4%
Other values (48)	33486	27.6%

coach
Text

Missing

Distinct	5651
Distinct (%)	68.7%
Missing	2891
Missing (%)	26.0%
Memory size	86.9 KiB

Length

Max length	349
Median length	229
Mean length	40.863415
Min length	5

Characters and Unicode

Total characters	335979
Distinct characters	108
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4807 ?
Unique (%)	58.5%

Sample

1st row	Gevorg Aleksanyan (ARM), father
2nd row	Personal: Martin Alekhanyan (ARM).<br>National: Armen Babalaryan (ARM)
3rd row	National: Habetnak Kurghinyan
4th row	National: Habetnak Kurghinyan (ARM)
5th row	Personal: Brent Vallance (AUS)

Value	Count	Frequency (%)
national	3974	8.9%
personal	2580	5.8%
club	1014	2.3%
usa	694	1.6%
fra	493	1.1%
esp	469	1.1%
ita	456	1.0%
gbr	416	0.9%
aus	410	0.9%
ger	399	0.9%
Other values (8746)	33536	75.5%

Most occurring characters

Value	Count	Frequency (%)
	36369	10.8%
a	28951	8.6%
n	18966	5.6%
o	18245	5.4%
e	17632	5.2%
l	17239	5.1%
i	17178	5.1%
r	15285	4.5%
t	10540	3.1%
)	10049	3.0%
Other values (98)	145525	43.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	335979	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	36369	10.8%
a	28951	8.6%
n	18966	5.6%
o	18245	5.4%
e	17632	5.2%
l	17239	5.1%
i	17178	5.1%
r	15285	4.5%
t	10540	3.1%
)	10049	3.0%
Other values (98)	145525	43.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	335979	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	36369	10.8%
a	28951	8.6%
n	18966	5.6%
o	18245	5.4%
e	17632	5.2%
l	17239	5.1%
i	17178	5.1%
r	15285	4.5%
t	10540	3.1%
)	10049	3.0%
Other values (98)	145525	43.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	335979	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	36369	10.8%
a	28951	8.6%
n	18966	5.6%
o	18245	5.4%
e	17632	5.2%
l	17239	5.1%
i	17178	5.1%
r	15285	4.5%
t	10540	3.1%
)	10049	3.0%
Other values (98)	145525	43.3%

reason
Text

Missing

Distinct	5734
Distinct (%)	98.1%
Missing	5267
Missing (%)	47.4%
Memory size	86.9 KiB

Length

Max length	972
Median length	582
Mean length	188.9362
Min length	10

Characters and Unicode

Total characters	1104521
Distinct characters	108
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5673 ?
Unique (%)	97.0%

Sample

1st row	He followed his father and his uncle into the sport
2nd row	While doing karate he noticed wrestlers training and decided to give it a try. He also tried judo but his father, a former wrestler, did not allow him to do both, so he chose wrestling. (sport.mediamax.am, 10 July 2017)
3rd row	“My family did not like wrestling very much. At first I wanted to do boxing but my older friends advised me to go to wrestling training, and after a week, I started to like the sport.” (myInfo)
4th row	"I was thrown over [an argument about] a Pokemon card and wanted to learn to throw immediately." (Athlete, 25 Jun 2024)
5th row	“I started running when I was in primary school, like we have junior championships. It's where I started running and it’s where I started to notice that, if I work hard I will be a great athlete.” (olympics.com, 24 Apr 2024)

Value	Count	Frequency (%)
the	7488	3.8%
to	7222	3.6%
i	6225	3.1%
and	6063	3.1%
a	5332	2.7%
was	4732	2.4%
in	4089	2.1%
her	3578	1.8%
his	2612	1.3%
she	2417	1.2%
Other values (10902)	148635	74.9%

Most occurring characters

Value	Count	Frequency (%)
	192598	17.4%
e	95648	8.7%
t	78260	7.1%
a	69853	6.3%
o	64792	5.9%
i	58234	5.3%
n	57875	5.2%
s	50759	4.6%
r	50467	4.6%
h	45414	4.1%
Other values (98)	340621	30.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1104521	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	192598	17.4%
e	95648	8.7%
t	78260	7.1%
a	69853	6.3%
o	64792	5.9%
i	58234	5.3%
n	57875	5.2%
s	50759	4.6%
r	50467	4.6%
h	45414	4.1%
Other values (98)	340621	30.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1104521	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	192598	17.4%
e	95648	8.7%
t	78260	7.1%
a	69853	6.3%
o	64792	5.9%
i	58234	5.3%
n	57875	5.2%
s	50759	4.6%
r	50467	4.6%
h	45414	4.1%
Other values (98)	340621	30.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1104521	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	192598	17.4%
e	95648	8.7%
t	78260	7.1%
a	69853	6.3%
o	64792	5.9%
i	58234	5.3%
n	57875	5.2%
s	50759	4.6%
r	50467	4.6%
h	45414	4.1%
Other values (98)	340621	30.8%

hero
Text

Missing

Distinct	2456
Distinct (%)	74.1%
Missing	7798
Missing (%)	70.2%
Memory size	86.9 KiB

Length

Max length	984
Median length	626
Mean length	242.18069
Min length	7

Characters and Unicode

Total characters	802829
Distinct characters	97
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2172 ?
Unique (%)	65.5%

Sample

1st row	Footballer Zinedine Zidane (FRA), World Cup winner (1998) and European champion (2000) with France, won the Champions League as a player and three times as a manager with Real Madrid, three-time FIFA World Player of the Year
2nd row	Wrestler Armen Nazaryan (ARM, BUL), two-time Olympic champion (1996, 2000) and 2004 bronze medallist. Eight-time world championship medallist (three gold, two silver, three bronze)
3rd row	Race walker Luis Fernando Lopez (COL), four-time Olympian (2004, 2008, 2012, 2016), 2011 world champion (20km walk)
4th row	Boxer Muhammad Ali, born Cassius Clay (USA), former undisputed heavyweight champion of the world, 1960 Olympic champion (light heavyweight), nicknamed 'The Greatest' and regarded as one of the most significant sports figures of the 20th century
5th row	Sprinter Shelly-Ann Fraser-Pryce (JAM), three time Olympic champion (four silver, one bronze), 16-time world championship medallist (10 gold, five silver, one bronze). In the 100m, two-time Olympic champion (2008, 2012), five-time world champion (2009, 2013, 2015, 2019, 2022). </p><p>"Shelly-Ann, she is consistent. She is a mother but she still loves what she is doing and she is still performing as she did before." (Tales of Hagie Drammeh Youtube, 16 Jan 2023)</p><p>Sprinter Marie-Josee Ta Lou (CIV), three fourth places at the Olympic Games (2016, 2020), double world silver medallist (100m-200m) in 2017, world bronze medallist in 2019 (100m)

Value	Count	Frequency (%)
medallist	4415	3.9%
olympic	3499	3.1%
world	3457	3.1%
silver	3170	2.8%
gold	3065	2.7%
champion	2680	2.4%
bronze	2613	2.3%
one	2075	1.9%
championship	1882	1.7%
two	1786	1.6%
Other values (7611)	83138	74.4%

Most occurring characters

Value	Count	Frequency (%)
	108628	13.5%
e	59125	7.4%
i	49911	6.2%
l	39911	5.0%
o	38969	4.9%
a	38372	4.8%
t	35045	4.4%
r	33949	4.2%
n	33638	4.2%
m	29063	3.6%
Other values (87)	336218	41.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	802829	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	108628	13.5%
e	59125	7.4%
i	49911	6.2%
l	39911	5.0%
o	38969	4.9%
a	38372	4.8%
t	35045	4.4%
r	33949	4.2%
n	33638	4.2%
m	29063	3.6%
Other values (87)	336218	41.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	802829	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	108628	13.5%
e	59125	7.4%
i	49911	6.2%
l	39911	5.0%
o	38969	4.9%
a	38372	4.8%
t	35045	4.4%
r	33949	4.2%
n	33638	4.2%
m	29063	3.6%
Other values (87)	336218	41.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	802829	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	108628	13.5%
e	59125	7.4%
i	49911	6.2%
l	39911	5.0%
o	38969	4.9%
a	38372	4.8%
t	35045	4.4%
r	33949	4.2%
n	33638	4.2%
m	29063	3.6%
Other values (87)	336218	41.9%

influence
Text

Missing

Distinct	1529
Distinct (%)	71.0%
Missing	8958
Missing (%)	80.6%
Memory size	86.9 KiB

Length

Max length	756
Median length	517
Mean length	81.467285
Min length	5

Characters and Unicode

Total characters	175562
Distinct characters	96
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1497 ?
Unique (%)	69.5%

Sample

1st row	His father, Gevorg Aleksanyan
2nd row	"My coach Luke Preston. We've been a team for the last 12 years." (Athlete, 25 Jun 2024)
3rd row	Momodou Lamin Kujabi, a former international athlete from The Gambia who was once his physical education teacher
4th row	Her parents
5th row	Fictional boxer Rocky Balboa from the "Rocky" movie series. "I saw the entire Rocky saga with my father, and I said, 'Wow. I want to do what he does, I want to be just as good’. I even told my parents that I wanted to be a boxer... Although I didn't go into boxing, the truth is that Rocky Balboa taught me to be someone, and I always think that if he went from street fights to being world champion, I could do something like that too." (heraldodemexico.com.mx, 2 Aug 2021)

Value	Count	Frequency (%)
and	1220	4.0%
her	1089	3.5%
his	927	3.0%
my	669	2.2%
me	668	2.2%
the	658	2.1%
to	646	2.1%
i	608	2.0%
coach	584	1.9%
in	415	1.4%
Other values (4814)	23250	75.6%

Most occurring characters

Value	Count	Frequency (%)
	28604	16.3%
e	16185	9.2%
a	11717	6.7%
t	9863	5.6%
r	8831	5.0%
o	8804	5.0%
i	8440	4.8%
n	8359	4.8%
s	7694	4.4%
h	7670	4.4%
Other values (86)	59395	33.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	175562	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	28604	16.3%
e	16185	9.2%
a	11717	6.7%
t	9863	5.6%
r	8831	5.0%
o	8804	5.0%
i	8440	4.8%
n	8359	4.8%
s	7694	4.4%
h	7670	4.4%
Other values (86)	59395	33.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	175562	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	28604	16.3%
e	16185	9.2%
a	11717	6.7%
t	9863	5.6%
r	8831	5.0%
o	8804	5.0%
i	8440	4.8%
n	8359	4.8%
s	7694	4.4%
h	7670	4.4%
Other values (86)	59395	33.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	175562	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	28604	16.3%
e	16185	9.2%
a	11717	6.7%
t	9863	5.6%
r	8831	5.0%
o	8804	5.0%
i	8440	4.8%
n	8359	4.8%
s	7694	4.4%
h	7670	4.4%
Other values (86)	59395	33.8%

philosophy
Text

Missing

Distinct	2761
Distinct (%)	99.2%
Missing	8330
Missing (%)	75.0%
Memory size	86.9 KiB

Length

Max length	954
Median length	410
Mean length	119.84585
Min length	1

Characters and Unicode

Total characters	333531
Distinct characters	97
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2749 ?
Unique (%)	98.8%

Sample

1st row	"Wrestling is my life." (mediamax.am. 18 May 2016)
2nd row	"To become a good athlete, you first have to be a good person." (ankakh.com, 6 Oct 2018)
3rd row	“Nothing is impossible, set goals in front of you, fight and achieve it.” (Instagram, 13 May 2023)
4th row	"If you believe in yourself, never be discouraged." (worldathletics.org, 17 Dec 2019)
5th row	"What does not kill you makes you stronger." (Athlete, 7 Jul 2024)

Value	Count	Frequency (%)
the	2043	3.5%
to	1910	3.3%
you	1638	2.8%
and	1537	2.6%
i	1316	2.3%
is	1140	2.0%
a	977	1.7%
it	799	1.4%
in	756	1.3%
2024	665	1.1%
Other values (5252)	45441	78.0%

Most occurring characters

Value	Count	Frequency (%)
	55462	16.6%
e	27715	8.3%
t	22126	6.6%
o	20614	6.2%
a	17924	5.4%
n	16475	4.9%
i	15036	4.5%
s	13399	4.0%
r	13191	4.0%
h	10641	3.2%
Other values (87)	120948	36.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	333531	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	55462	16.6%
e	27715	8.3%
t	22126	6.6%
o	20614	6.2%
a	17924	5.4%
n	16475	4.9%
i	15036	4.5%
s	13399	4.0%
r	13191	4.0%
h	10641	3.2%
Other values (87)	120948	36.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	333531	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	55462	16.6%
e	27715	8.3%
t	22126	6.6%
o	20614	6.2%
a	17924	5.4%
n	16475	4.9%
i	15036	4.5%
s	13399	4.0%
r	13191	4.0%
h	10641	3.2%
Other values (87)	120948	36.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	333531	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	55462	16.6%
e	27715	8.3%
t	22126	6.6%
o	20614	6.2%
a	17924	5.4%
n	16475	4.9%
i	15036	4.5%
s	13399	4.0%
r	13191	4.0%
h	10641	3.2%
Other values (87)	120948	36.3%

sporting_relatives
Text

Missing

Distinct	2517
Distinct (%)	> 99.9%
Missing	8595
Missing (%)	77.3%
Memory size	86.9 KiB

Length

Max length	981
Median length	495
Mean length	181.16322
Min length	22

Characters and Unicode

Total characters	456169
Distinct characters	100
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2516 ?
Unique (%)	99.9%

Sample

1st row	Uncle, Roman Amoyan (wrestling), 2008 Olympic bronze medallist and two-time European champion in Greco-Roman
2nd row	Uncle, Salvador "Chava" Sabrino (diving), finished 11th in the 10m platform event at the 1980 Olympic Games and is head coach for the Australian national team
3rd row	Partner, Iker Casas (taekwondo), won a bronze medal at the 2018 Central American and Caribbean Games (63kg) and a silver at the 2021 Pan American Championships (68kg)
4th row	Father, Manuel Verde (boxing), competed for Mexico in the men's light heavyweight division at the Barcelona 1992 Olympic Games
5th row	Brother Jair (athletics), 2024 National Championships high jump silver medallist

Value	Count	Frequency (%)
the	3157	4.9%
in	2729	4.2%
at	1957	3.0%
and	1498	2.3%
for	982	1.5%
world	909	1.4%
championships	747	1.2%
olympic	697	1.1%
games	689	1.1%
a	685	1.1%
Other values (9228)	50782	78.3%

Most occurring characters

Value	Count	Frequency (%)
	62498	13.7%
e	36702	8.0%
a	31259	6.9%
i	26127	5.7%
n	25585	5.6%
t	24974	5.5%
r	22480	4.9%
o	21875	4.8%
l	18555	4.1%
s	18031	4.0%
Other values (90)	168083	36.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	456169	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	62498	13.7%
e	36702	8.0%
a	31259	6.9%
i	26127	5.7%
n	25585	5.6%
t	24974	5.5%
r	22480	4.9%
o	21875	4.8%
l	18555	4.1%
s	18031	4.0%
Other values (90)	168083	36.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	456169	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	62498	13.7%
e	36702	8.0%
a	31259	6.9%
i	26127	5.7%
n	25585	5.6%
t	24974	5.5%
r	22480	4.9%
o	21875	4.8%
l	18555	4.1%
s	18031	4.0%
Other values (90)	168083	36.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	456169	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	62498	13.7%
e	36702	8.0%
a	31259	6.9%
i	26127	5.7%
n	25585	5.6%
t	24974	5.5%
r	22480	4.9%
o	21875	4.8%
l	18555	4.1%
s	18031	4.0%
Other values (90)	168083	36.8%

ritual
Text

Missing

Distinct	847
Distinct (%)	98.8%
Missing	10256
Missing (%)	92.3%
Memory size	86.9 KiB

Length

Max length	857
Median length	291
Mean length	124.78646
Min length	7

Characters and Unicode

Total characters	106942
Distinct characters	89
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	839 ?
Unique (%)	97.9%

Sample

1st row	In competition she wears a ring or earrings her family gave her
2nd row	When she is preparing for a competition, applying her makeup and combing her hair, she watches the film Hercules. "Once I’m ready I listen to music that makes me dance a little.” (intlgymnast.com)
3rd row	She is a Buddhist
4th row	"I believe a lot in energies and collaboration with the universe. I give thanks to God in advance for my future success." (Athlete, 1 Jul 2024)
5th row	Before competition he listens to ‘Stardust Crusaders’ theme from JoJo's Bizarre Adventure (manga). During a race he has Vivaldi's 'The Four Seasons' in his head

Value	Count	Frequency (%)
to	789	4.1%
the	742	3.8%
a	596	3.1%
i	593	3.1%
and	581	3.0%
before	404	2.1%
her	300	1.5%
in	287	1.5%
on	252	1.3%
my	250	1.3%
Other values (2968)	14610	75.3%

Most occurring characters

Value	Count	Frequency (%)
	18553	17.3%
e	10146	9.5%
t	7484	7.0%
a	6599	6.2%
o	6337	5.9%
i	5426	5.1%
s	5380	5.0%
n	5286	4.9%
r	4702	4.4%
h	4167	3.9%
Other values (79)	32862	30.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	106942	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	18553	17.3%
e	10146	9.5%
t	7484	7.0%
a	6599	6.2%
o	6337	5.9%
i	5426	5.1%
s	5380	5.0%
n	5286	4.9%
r	4702	4.4%
h	4167	3.9%
Other values (79)	32862	30.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	106942	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	18553	17.3%
e	10146	9.5%
t	7484	7.0%
a	6599	6.2%
o	6337	5.9%
i	5426	5.1%
s	5380	5.0%
n	5286	4.9%
r	4702	4.4%
h	4167	3.9%
Other values (79)	32862	30.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	106942	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	18553	17.3%
e	10146	9.5%
t	7484	7.0%
a	6599	6.2%
o	6337	5.9%
i	5426	5.1%
s	5380	5.0%
n	5286	4.9%
r	4702	4.4%
h	4167	3.9%
Other values (79)	32862	30.7%

other_sports
Text

Missing

Distinct	1046
Distinct (%)	98.7%
Missing	10053
Missing (%)	90.5%
Memory size	86.9 KiB

Length

Max length	655
Median length	243
Mean length	109.41887
Min length	6

Characters and Unicode

Total characters	115984
Distinct characters	88
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1038 ?
Unique (%)	97.9%

Sample

1st row	Competed in marathon swimming at London 2012. Finished 20th in the 10km. She also competed in the Marathon Swimming World Cup circuit and at multiple world championships
2nd row	He was 2019 sambo world champion at 82kg (held in Cheongju, Republic of Korea)
3rd row	Football: Plays as a striker for the Malawi national team. Won the 2023 COSAFA Women's Championship final
4th row	Equestrian jumping: Represented Singapore at international youth level and competed in the individual and team events at the 2010 Youth Olympic Games in Singapore
5th row	Kurash: Silver medallist at the 2016 World Junior Championships

Value	Count	Frequency (%)
in	1203	6.6%
the	1095	6.0%
at	694	3.8%
and	500	2.7%
championships	288	1.6%
world	286	1.6%
competed	260	1.4%
for	251	1.4%
played	250	1.4%
a	249	1.4%
Other values (2415)	13194	72.2%

Most occurring characters

Value	Count	Frequency (%)
	17215	14.8%
e	9268	8.0%
a	8144	7.0%
n	7557	6.5%
i	6993	6.0%
t	6495	5.6%
o	6007	5.2%
l	4877	4.2%
s	4821	4.2%
r	4414	3.8%
Other values (78)	40193	34.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	115984	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	17215	14.8%
e	9268	8.0%
a	8144	7.0%
n	7557	6.5%
i	6993	6.0%
t	6495	5.6%
o	6007	5.2%
l	4877	4.2%
s	4821	4.2%
r	4414	3.8%
Other values (78)	40193	34.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	115984	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	17215	14.8%
e	9268	8.0%
a	8144	7.0%
n	7557	6.5%
i	6993	6.0%
t	6495	5.6%
o	6007	5.2%
l	4877	4.2%
s	4821	4.2%
r	4414	3.8%
Other values (78)	40193	34.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	115984	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	17215	14.8%
e	9268	8.0%
a	8144	7.0%
n	7557	6.5%
i	6993	6.0%
t	6495	5.6%
o	6007	5.2%
l	4877	4.2%
s	4821	4.2%
r	4414	3.8%
Other values (78)	40193	34.7%

Interactions

Correlations

	code	current	function	gender	height	weight
code	1.000	0.000	0.000	0.000	0.073	0.027
current	0.000	1.000	0.000	0.005	1.000	1.000
function	0.000	0.000	1.000	0.005	0.004	0.000
gender	0.000	0.005	0.005	1.000	0.349	0.141
height	0.073	1.000	0.004	0.349	1.000	0.149
weight	0.027	1.000	0.000	0.141	0.149	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

	code	current	name	name_short	name_tv	gender	function	country_code	country	country_long	nationality	nationality_long	nationality_code	height	disciplines	events	birth_date	birth_place	birth_country	residence_place	residence_country	nickname	hobbies	occupation	education	family	lang	coach	reason	hero	influence	philosophy	sporting_relatives	ritual	other_sports
0	1532872	True	ALEKSANYAN Artur	ALEKSANYAN A	Artur ALEKSANYAN	Male	Athlete	ARM	Armenia	Armenia	Armenia	Armenia	ARM	0.0	['Wrestling']	["Men's Greco-Roman 97kg"]	1991-10-21	GYUMRI	Armenia	GYUMRI	Armenia	White Bear	Playing and watching football	Athlete	Graduated from Shirak State University (Gyumri, ARM)	Father, Gevorg Aleksanyan	Armenian, English, Russian	Gevorg Aleksanyan (ARM), father	He followed his father and his uncle into the sport	Footballer Zinedine Zidane (FRA), World Cup winner (1998) and European champion (2000) with France, won the Champions League as a player and three times as a manager with Real Madrid, three-time FIFA World Player of the Year	His father, Gevorg Aleksanyan	"Wrestling is my life." (mediamax.am. 18 May 2016)	NaN	NaN	NaN
1	1532873	True	AMOYAN Malkhas	AMOYAN M	Malkhas AMOYAN	Male	Athlete	ARM	Armenia	Armenia	Armenia	Armenia	ARM	0.0	['Wrestling']	["Men's Greco-Roman 77kg"]	1999-01-22	YEREVAN	Armenia	YEREVAN	Armenia	NaN	NaN	NaN	NaN	NaN	Armenian	NaN	NaN	NaN	NaN	"To become a good athlete, you first have to be a good person." (ankakh.com, 6 Oct 2018)	Uncle, Roman Amoyan (wrestling), 2008 Olympic bronze medallist and two-time European champion in Greco-Roman	NaN	NaN
2	1532874	True	GALSTYAN Slavik	GALSTYAN S	Slavik GALSTYAN	Male	Athlete	ARM	Armenia	Armenia	Armenia	Armenia	ARM	0.0	['Wrestling']	["Men's Greco-Roman 67kg"]	1996-12-21	NaN	NaN	YEREVAN	Armenia	NaN	NaN	NaN	NaN	NaN	Armenian	Personal: Martin Alekhanyan (ARM).<br>National: Armen Babalaryan (ARM)	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	1532944	True	HARUTYUNYAN Arsen	HARUTYUNYAN A	Arsen HARUTYUNYAN	Male	Athlete	ARM	Armenia	Armenia	Armenia	Armenia	ARM	0.0	['Wrestling']	["Men's Freestyle 57kg"]	1999-11-22	MASIS	Armenia	YEREVAN	Armenia	NaN	NaN	Athlete	Graduated with a Master's degree from the Armenian State Institute of Physical Culture and Sport (2023)	Wife, Diana (married October 2022). Daughter, Marias (born 2023)	Armenian	National: Habetnak Kurghinyan	While doing karate he noticed wrestlers training and decided to give it a try. He also tried judo but his father, a former wrestler, did not allow him to do both, so he chose wrestling. (sport.mediamax.am, 10 July 2017)	Wrestler Armen Nazaryan (ARM, BUL), two-time Olympic champion (1996, 2000) and 2004 bronze medallist. Eight-time world championship medallist (three gold, two silver, three bronze)	NaN	“Nothing is impossible, set goals in front of you, fight and achieve it.” (Instagram, 13 May 2023)	NaN	NaN	NaN
4	1532945	True	TEVANYAN Vazgen	TEVANYAN V	Vazgen TEVANYAN	Male	Athlete	ARM	Armenia	Armenia	Armenia	Armenia	ARM	0.0	['Wrestling']	["Men's Freestyle 65kg"]	1999-10-27	POKR VEDI	Armenia	NaN	Armenia	NaN	NaN	Athlete	Studied at the Armenian State Institute of Physical Culture and Sport (Yerevan, ARM)	Wife, Sona (married November 2023)	Armenian, Russian	National: Habetnak Kurghinyan (ARM)	“My family did not like wrestling very much. At first I wanted to do boxing but my older friends advised me to go to wrestling training, and after a week, I started to like the sport.” (myInfo)	NaN	NaN	NaN	NaN	NaN	NaN
5	1532951	True	ARENAS Lorena	ARENAS L	Lorena ARENAS	Female	Athlete	COL	Colombia	Colombia	Colombia	Colombia	COL	162.0	['Athletics']	["Women's 20km Race Walk", 'Marathon Race Walk Relay Mixed']	1993-09-17	PEREIRA	Colombia	MELBOURNE	Australia	NaN	NaN	Athlete	Physical Education at Jaime Isaza Cadavid Colombian Polytechnic, Medellin (COL)	Father, Jose Otoniel. Mother, Maria Rudy. Has three siblings	Spanish	Personal: Brent Vallance (AUS)	NaN	Race walker Luis Fernando Lopez (COL), four-time Olympian (2004, 2008, 2012, 2016), 2011 world champion (20km walk)	NaN	NaN	NaN	In competition she wears a ring or earrings her family gave her	NaN
6	1533112	True	McKENZIE Ashley	McKENZIE A	Ashley McKENZIE	Male	Athlete	JAM	Jamaica	Jamaica	Jamaica	Jamaica	JAM	0.0	['Judo']	['Men -60 kg']	1989-07-17	LONDON	Great Britain	CAMBERLEY	Great Britain	Bad Boy	Music	Athlete	NaN	One daughter, Lana-Rose, who lives in France	English	Personal and National: Luke Preston (GBR)	"I was thrown over [an argument about] a Pokemon card and wanted to learn to throw immediately." (Athlete, 25 Jun 2024)	Boxer Muhammad Ali, born Cassius Clay (USA), former undisputed heavyweight champion of the world, 1960 Olympic champion (light heavyweight), nicknamed 'The Greatest' and regarded as one of the most significant sports figures of the 20th century	"My coach Luke Preston. We've been a team for the last 12 years." (Athlete, 25 Jun 2024)	NaN	NaN	NaN	NaN
7	1533136	True	BASS BITTAYE Gina Mariam	BASS BITTAYE GM	Gina Mariam BASS BITTAYE	Female	Athlete	GAM	Gambia	Gambia	Gambia	Gambia	GAM	161.0	['Athletics']	["Women's 100m", "Women's 200m"]	1995-05-03	TUBAKUTA	Gambia	NaN	NaN	Earlier in her career she was nicknamed the 'Poor Olympian' due to the financial challenges she faced	NaN	Athlete, police officer (sub-inspector)	NaN	Husband, Mustapha Bittaye - physical education lecturer and football referee (married October 2023). One sister and two brothers	English, French	Personal: Christophe Belliard (FRA)	“I started running when I was in primary school, like we have junior championships. It's where I started running and it’s where I started to notice that, if I work hard I will be a great athlete.” (olympics.com, 24 Apr 2024)	Sprinter Shelly-Ann Fraser-Pryce (JAM), three time Olympic champion (four silver, one bronze), 16-time world championship medallist (10 gold, five silver, one bronze). In the 100m, two-time Olympic champion (2008, 2012), five-time world champion (2009, 2013, 2015, 2019, 2022). </p><p>"Shelly-Ann, she is consistent. She is a mother but she still loves what she is doing and she is still performing as she did before." (Tales of Hagie Drammeh Youtube, 16 Jan 2023)</p><p>Sprinter Marie-Josee Ta Lou (CIV), three fourth places at the Olympic Games (2016, 2020), double world silver medallist (100m-200m) in 2017, world bronze medallist in 2019 (100m)	NaN	"If you believe in yourself, never be discouraged." (worldathletics.org, 17 Dec 2019)	NaN	NaN	NaN
8	1533176	True	CAMARA Ebrahima	CAMARA E	Ebrahima CAMARA	Male	Athlete	GAM	Gambia	Gambia	Gambia	Gambia	GAM	178.0	['Athletics']	["Men's 100m"]	1996-09-18	BUNDUNG	Gambia	ANGERS	France	NaN	Running, watching movies, football, chatting with friends	Athlete, prison officer	NaN	Married. One daughter. Has three brothers	Arabic, English, French, Mandinka, Wolof	Personal: Christophe Belliard (FRA)	"I love running and I was fast a child." (Athlete, 7 Jul 2024)	Sprinter Gina Mariam Bass Bittaye (GAM), two-time Olympian (Rio 2016, Tokyo 2020), 2019 World Championships 200m finalist, four-time African championships medallist (two gold, two bronze), four-time African Games medallist (three gold, one silver)	Momodou Lamin Kujabi, a former international athlete from The Gambia who was once his physical education teacher	"What does not kill you makes you stronger." (Athlete, 7 Jul 2024)	NaN	NaN	NaN
9	1533188	True	RUEDA SANTOS Lizeth	RUEDA SANTOS L	Lizeth RUEDA SANTOS	Female	Athlete	MEX	Mexico	Mexico	Mexico	Mexico	MEX	0.0	['Triathlon']	["Women's Individual"]	1994-03-07	GUADALAJARA	Mexico	XALAPA	Mexico	NaN	NaN	Athlete	Studied Medicine at the University of Guadalajara (MEX)	NaN	Spanish	Personal: Eugenio Chimal (MEX)	Was a competitive swimmer from age 12 and went on to race internationally in marathon swimming	NaN	NaN	NaN	NaN	NaN	Competed in marathon swimming at London 2012. Finished 20th in the 10km. She also competed in the Marathon Swimming World Cup circuit and at multiple world championships

	code	current	name	name_short	name_tv	gender	function	country_code	country	country_long	nationality	nationality_long	nationality_code	height	weight	disciplines	events	birth_date	birth_place	birth_country	residence_place	residence_country	nickname	hobbies	occupation	education	family	lang	coach	reason	hero	influence	philosophy	sporting_relatives	ritual	other_sports
11103	4979790	True	INSIXIENGMAY Steven	INSIXIENGMAY S	Steven INSIXIENGMAY	Male	Athlete	LAO	Lao PDR	Lao People's Democratic Republic	Lao PDR	Lao People's Democratic Republic	LAO	0.0	0.0	['Swimming']	["Men's 100m Breaststroke"]	2004-01-21	NaN	NaN	WINSTON-SALEM, NC	United States	NaN	NaN	Athlete, student	Studying Business at the University of Georgia (Athens, GA, USA)	Father, Dalavong. Mother, Sengphet Sayaphanthong	English	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
11104	4980004	True	van de WIEL Anne	van de WIEL A	Anne van de WIEL	Female	Athlete	NED	Netherlands	Netherlands	Netherlands	Netherlands	NED	168.0	0.0	['Athletics']	["Women's 4 x 400m Relay"]	1997-06-04	NaN	NaN	ROTTERDAM	Netherlands	NaN	NaN	Athlete, student	Sociology - Erasmus University Rotterdam, Netherlands	NaN	Dutch, English	National: Laurent Meuwly.<br>Personal: Niels Hanegraaf	She got involved in athletics along with her twin sister Myke. "We were pretty boisterous kids. An uncle, whose two sons did athletics, suggested to our mother that we join an athletics club. We enjoyed it so much that we're still at it today." (erasmusmagazine.nl, 6 Jun 2018)	NaN	NaN	NaN	Sister, Myke van de Wiel (athletics), is a two-time Dutch national champion in the heptathlon (2018, 2021) and won an indoor national title in the 200m in 2021	NaN	NaN
11105	4982175	True	JOSEPH Elijah	JOSEPH E	Elijah JOSEPH	Male	Athlete	TTO	Trinidad and Tobago	Trinidad and Tobago	Trinidad and Tobago	Trinidad and Tobago	TTO	177.0	0.0	['Athletics']	["Men's 4 x 400m Relay"]	2001-07-03	NaN	NaN	NaN	NaN	NaN	NaN	Athlete	NaN	NaN	English	Personal: Ebert Joseph (TTO)	NaN	NaN	NaN	NaN	NaN	NaN	NaN
11106	4982762	True	HOMAN Khrystyna	HOMAN K	Khrystyna HOMAN	Female	Athlete	UKR	Ukraine	Ukraine	Ukraine	Ukraine	UKR	0.0	0.0	['Judo']	['Women +78 kg']	1999-01-31	SLAVUTYCH	Ukraine	KIEV	Ukraine	Danger	Playing the guitar, eating delicious food, playing basketball	Athlete	Graduated with a Bachelor's degree in Physical Culture and Sports in December 2021	Mother and one younger brother	Ukrainian	National: Quedjau Nhabali (UKR).<br>Personal: Oleg Kopylov (UKR).<br>Club: Sergey Dubrova (UKR)	Because her mother raised the idea	NaN	"Quedjau Nhabali is always there with the right words. Oleg Kopylov is the first coach whose opinion is important to me." (Athlete, 9 Jul 2024)	NaN	NaN	NaN	She likes MMA
11107	4983537	True	CHELANGAT Annet Chemengich	CHELANGAT AC	Annet Chemengich CHELANGAT	Female	Athlete	UGA	Uganda	Uganda	Uganda	Uganda	UGA	174.0	0.0	['Athletics']	["Women's 10,000m"]	1993-07-29	NaN	Uganda	NaN	Uganda	NaN	NaN	Athlete	NaN	NaN	English	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
11108	4986655	True	ADA ETO Sefora	ADA ETO S	Sefora ADA ETO	Female	Athlete	GEQ	Equatorial Guinea	Equatorial Guinea	Equatorial Guinea	Equatorial Guinea	GEQ	165.0	0.0	['Athletics']	["Women's 100m"]	2003-06-11	ABIERE ESATOP, NSOK NSOMO	Equatorial Guinea	MALABO	Equatorial Guinea	NaN	NaN	NaN	NaN	NaN	Spanish	Personal: Feliciano Javier y Mananses Mba Micha	NaN	NaN	NaN	NaN	NaN	NaN	NaN
11109	9460001	True	LIUZZI Emanuela	LIUZZI E	Emanuela LIUZZI	Female	Athlete	ITA	Italy	Italy	NaN	NaN	NaN	0.0	0.0	['Wrestling']	["Women's Freestyle 50kg"]	2000-04-27	NaN	NaN	NaN	NaN	NaN	NaN	Athlete	NaN	NaN	Italian	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
11110	1972077	False	BOERS Isayah	NaN	NaN	Male	Athlete	NED	Netherlands	Netherlands	Netherlands	Netherlands	NED	NaN	NaN	[Athletics]	[4 x 400m Relay Mixed]	1999-06-19	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
11111	1899865	False	STAUT Kevin	NaN	NaN	Male	Athlete	FRA	France	France	France	France	FRA	NaN	NaN	[Equestrian]	[Jumping Team]	1980-11-15	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
11112	1924402	False	CARVELL Charlie	NaN	NaN	Male	Athlete	GBR	Great Britain	Great Britain	Great Britain	Great Britain	GBR	NaN	NaN	[Athletics]	[Men's 4 x 400m Relay]	2004-06-30	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories